Abstract
As the oldest, but least understood sensory system in evolution, the olfactory system represents one of the most challenging research targets in sensory neurobiology. Although a large number of computational models of the olfactory system have been proposed, they do not account for the diversity in physiology, connectivity of local neurons, and several recent discoveries in the insect antennal lobe, a major olfactory organ in insects. Recent studies revealed that the response of some projection neurons were reduced by application of a GABA antagonist, and that insects are sensitive to odor pulse frequency. To account for these observations, we propose a spiking neural circuit model of the insect antennal lobe. Based on recent anatomical and physiological studies, we included three sub-types of local neurons as well as synaptic short-term depression (STD) in the model and showed that the interaction between STD and local neurons resulted in frequency-sensitive responses. We further discovered that the unexpected response of the projection neurons to the GABA antagonist is the result of complex interactions between STD and presynaptic inhibition, which is required for enhancing sensitivity to odor stimuli. Finally, we found that odor discrimination is improved if the innervation of the local neurons in the glomeruli follows a specific pattern. Our findings suggest that STD, presynaptic inhibition and diverse physiology and connectivity of local neurons are not independent properties, but they interact to play key roles in the function of antennal lobes.
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The work was supported by the Ministry of Science and Technology grants 101-2311-B-007-008-MY3, 107-2218-E007-033, and by the Higher Education Sprout Project funded by the Ministry of Science and Technology and Ministry of Education in Taiwan.
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Fig S1
The network dynamic is robust against the change of the dependence of the synaptic weights on presynaptic calcium concentration. We performed the model simulations with different dependences by changing the values of the power in Eq. 7 from 3.5 to 3.0 and 4.0. The simulations were all performed using the same seed number of the random number generator. This guaranteed that we compared the results based on the exact same realization and no noise or trial-to-trial variability was involved. (A) The firing rate profiles of the neurons in one glomerulus in response to the odor stimulus. (B) The firing rate profiles of PNs in every glomeruli in response to the odor stimuli with different pulse frequencies. (PNG 54 kb)
Fig S2
Schematics illustrating how to quantify similar odor discrimination. (A) The responses of PLNs to an odor A can be represented by a point on the multi-dimensional plot. First, we obtain ten points from ten trials of odor A and another ten points of similar but different odors. Now we can set a discrimination criterion by drawing a circle centered on an arbitrary point of odor A. Points that fall in the circle are classified as odor A and other points are not odor A. We can vary the radius of the circle and obtain different classification results. (B) For each criterion, we can calculate the true positive, true negative, false positive and false negative numbers, and construct a confusion matrix associated with this criterion. (PNG 10262 kb)
Fig S3
Schematics showing how STD reduces the amounts of neurotransmitters. The presynaptic calcium concentration [Ca2+] and STD variable D follow a similar dynamics. Both variables reduce during the stimulus while recover after the stimulus offset. (A) When the stimulus frequency is high, the level of [Ca2+] or D decays rapidly due to insufficient inter-stimulus intervals for recover. (B) When the stimulus frequency is low, longer inter-stimulus intervals lead to better recovery of [Ca2+] or D, and hence a slower decay. Therefore, by monitoring the decay rate of these variables, one can estimate the frequency of stimulus input. Furthermore, since the PN responses to the odor stimuli depend on the ORN-PN synaptic weights, which is the product of [Ca2+]3.5 and D (Eq. 7), the PN responses to repetitive odor pulses also follow a similar behavior with a decay rate dependent on the frequency of the odor pulses. (PNG 150 kb)
Fig S4
Schematics illustrating the effect of spontaneous local neurons (SLNs) on the presynaptic vesicle availability. (A) Some ORNs exhibit strong spontaneous activity. If the ORN-PN synapse is not targeted by SLNs, the vesicles in the presynaptic terminal are quickly depleted and the synapse is depressed. (B) If the ORN-PN synapse is targeted by SLNs, the presynaptic inhibition exhibited by SLNs reduces the level of presynaptic calcium, which in turn reduces the ability of vesicle release despite of the spontaneous activity in ORN. As a result, the synapse maintains abundant vesicles and is able to response to odor stimuli once SLNs is shut down. (PNG 15499 kb)
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Kao, KW., Lo, CC. Short term depression, presynaptic inhibition and local neuron diversity play key functional roles in the insect antennal lobe. J Comput Neurosci 48, 213–227 (2020). https://doi.org/10.1007/s10827-020-00747-4
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DOI: https://doi.org/10.1007/s10827-020-00747-4